Understanding Living Systems - Clairambault, Jean; Giacchero, Damien; Mascari, Jean-Francois
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Understanding Living Systems presents an integrated approach, covering mathematics, physics, computer science, biology and medicine. In this novel approach, the physiological structure is modeled at the level of n-categories (n-categories, n-functors, n-natural transformations, n-adjunctions etc.), the dynamics is modeled at the level of (n+h)-categories, and the evolution is modeled at the level of (n+h+k)categories. The pathological structure is modeled at the level of n-categories (n+n')-categories, the pathological repaired dynamics is modeled at the level of (n+n' + h+h')-categories and…mehr

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Produktbeschreibung
Understanding Living Systems presents an integrated approach, covering mathematics, physics, computer science, biology and medicine. In this novel approach, the physiological structure is modeled at the level of n-categories (n-categories, n-functors, n-natural transformations, n-adjunctions etc.), the dynamics is modeled at the level of (n+h)-categories, and the evolution is modeled at the level of (n+h+k)categories. The pathological structure is modeled at the level of n-categories (n+n')-categories, the pathological repaired dynamics is modeled at the level of (n+n' + h+h')-categories and the pathological evolution is modeled at the level of (n+n' + h+ h' + k+k')-categories. This new approach advances the field of computational modeling for biomedical engineers, computer scientists, physicians and mathematical researchers.
Autorenporträt
Dr. Jean Clairambault is Emeritus Senior Scientist and Director of Research for the Mathematical Models for Biology and Medicine (MAMBA) team at Institut National de Recherche en Informatique et en Automatique (INRIA), Paris, France. He received his Ph.D. in Mathematics (Analytical Geometry) from INRIA Paris and his M.D. from INRIA Paris. His research specialties include evolution of phenotypes in cancer cell populations ('cell Darwinism') towards drug resistance, physiologically structured partial differential equation models for cell population dynamics, pharmacotherapeutic optimization in oncology with regard to toxic side effects and drug resistance, and the cell division cycle and its physiological and pharmacological control in cell populations.